Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare destructive=true and idempotent=true, and the description corroborates rather than contradicts them: 'can't be undone' matches destructive, and 'every step is safe to repeat / call again with the same name' matches idempotent. It further adds error semantics (404 = no such dataset; 503 = partial failure with a retry recipe) and the auth requirement, which annotations do not cover.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the destructive scope before the alternative, then returns, then errors, then auth — a logical order with no filler. Every sentence carries actionable content; the return-key list is slightly redundant against the output schema but is compact enough not to count as waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive single-parameter tool it covers the full decision surface: what gets destroyed, irreversibility, confirmation duty, the non-destructive alternative, failure modes with recovery, and auth. The output schema exists, yet the inline return summary still helps the agent interpret partial-failure results (e.g., files_deleted vs saved_query_deleted).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single parameter, and the schema already explains that dataset_name is 'the dataset's `name`, as list_user_datasets shows it.' The description adds only the confirmation-time instruction to name the dataset, so the baseline 3 is appropriate — the schema does the heavy lifting here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Delete one of the user's own datasets completely') and enumerates exactly what is destroyed: schedule, built files, latest_url link, and saved query. It also names the sibling it is not (delete_scheduled_task) and the exact argument form that routes there, so an agent can distinguish it from the other delete_* tools without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use (full dataset removal) and when-not (to only stop builds and keep files, use delete_scheduled_task("ds:{email}:{name}")). It also adds a required procedural precondition — confirm with the user first, naming the dataset — which is guidance beyond mere routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.